Key result
Progression of cardiac autonomic neuropathy shifts the inverse power law index µ from the healthy condition (µ = 2) toward Gaussian statistics (µ = 3), with the scaling parameter δ decreasing from 0.650 in normal subjects to 0.543 in definite CAN.
Why the study?
To explore whether disease evolution in diabetes-induced cardiac autonomic neuropathy shifts the inverse power law index of crucial events toward Gaussian statistics to assess disease progression.
Does diffusion entropy analysis of heart rate variability detect the progression of cardiac autonomic neuropathy in diabetic patients?
Cross-Sectional
No
Does diffusion entropy analysis of heart rate variability detect the progression of cardiac autonomic neuropathy in diabetic patients?
Diffusion entropy analysis of heart rate variability provides a sensitive index for assessing the progression of cardiac autonomic neuropathy by detecting shifts in dynamical complexity.
Answers are grounded in this paper and cite their sources.
Diffusion entropy analysis of HRV may detect CAN progression in diabetes; leaves open its clinical utility pending prospective validation.
We review the literature to argue the importance of the occurrence of crucial events in the dynamics of physiological processes. Crucial events are interpreted as short time intervals of turbulence, and the time distance between two consecutive crucial events is a waiting time distribution density with an inverse power law (IPL) index μ, with μ < 3 generating non-stationary behavior. The non-stationary condition is characterized by two regimes of the IPL index: (a) perennial non-stationarity, with 1 < μ < 2 and (b) slow evolution toward the stationary regime, with 2 < μ < 3. Human heartbeats and brain dynamics belong to the latter regime, with healthy physiological processes tending to be closer to the border with the perennial non-stationary regime with μ = 2. The complexity of cognitive tasks is associated with the mental effort required to address a difficult task, which leads to an increase of μ with increasing task difficulty. On this basis we explore the conjecture that disease evolution leads the IPL index μ moving from the healthy condition μ = 2 toward the border with Gaussian statistics with μ = 3, as the disease progresses. Examining heart rate time series of patients affected by diabetes-induced autonomic neuropathy of varying severity, we find that the progression of cardiac autonomic neuropathy (CAN) indeed shifts μ from the border with perennial variability, μ = 2, to the border with Gaussian statistics, μ = 3 and provides a novel, sensitive index for assessing disease progression. We find that at the Gaussian border, the dynamical complexity of crucial events is replaced by Gaussian fluctuation with long-time memory.
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Jelinek et al. (2021) conducted a cross-sectional in Cardiac Autonomic Neuropathy in Type 2 Diabetes Mellitus. Progression of Cardiac Autonomic Neuropathy (CAN) vs. Normal/Control (no CAN) was evaluated on DEA scaling parameter (δ). Progression of cardiac autonomic neuropathy shifts the inverse power law index µ from the healthy condition (µ = 2) toward Gaussian statistics (µ = 3), with the scaling parameter δ decreasing from 0.650 in normal subjects to 0.543 in definite CAN.
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